身体成分分析:身体成分比例的细胞水平建模。

Z Wang, S B Heymsfield, F X Pi-Sunyer, D Gallagher, R N Pierson
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引用次数: 0

摘要

在过去的二十年中,我们在圣卢克罗斯福医院的研究小组努力的一个主要成果是身体成分模型的发展,包括细胞水平模型、基于身体成分比例的模型、全身钾模型、多成分模型和静息能量消耗-身体成分模型。这篇综述总结了这些模型,重点是成分比例,我们认为这是理解生长发育过程中人体成分以及对疾病和治疗的反应的基础。体内测量显示,在健康成人中,某些成分的比例变化很小,而且相对“稳定”,例如全身水/无脂肪质量和无脂肪质量密度。这些比率可以有效地应用于开发身体成分方法。相比之下,其他比率,如全身钾/无脂肪质量,在体内是高度可变的,因此对建立身体成分模型不太有用。为了理解控制这些成分比率变异性的机制,我们开发了8个细胞水平的比率模型,并从这些模型中导出了简化模型,这些模型将细胞外与细胞内水比(E/I)的比率作为主要决定因素。成人的E/I值差异很大。模型分析表明,通过将细胞水平模型与E/I值相关联,可以预测各体成分比的大小和变异性。因此,我们的方法提供了对成人身体成分比的新见解和更好的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Body composition analysis: Cellular level modeling of body component ratios.

During the past two decades, a major outgrowth of efforts by our research group at St. Luke's-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growth and development and in response to disease and treatments. In-vivo measurements reveal that in healthy adults some component ratios show minimal variability and are relatively 'stable', for example total body water/fat-free mass and fat-free mass density. These ratios can be effectively applied for developing body composition methods. In contrast, other ratios, such as total body potassium/fat-free mass, are highly variable in vivo and therefore are less useful for developing body composition models. In order to understand the mechanisms governing the variability of these component ratios, we have developed eight cellular level ratio models and from them we derived simplified models that share as a major determining factor the ratio of extracellular to intracellular water ratio (E/I). The E/I value varies widely among adults. Model analysis reveals that the magnitude and variability of each body component ratio can be predicted by correlating the cellular level model with the E/I value. Our approach thus provides new insights into and improved understanding of body composition ratios in adults.

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